The main “prognostic” coefficient \(\beta _{1,k}=2\)  for each covariate \(k\) . This is considered a strong covariate-outcome association. The interaction coefficient \(\beta _{2,k}=1\)  for each covariate \(k\) , indicating notable effect modification. We set the intercept \(\beta _0=5\) . Active treatments \(A\)  and \(B\)  are assumed to have the same set of effect modifiers with respect to the common comparator, and identical interaction coefficients for each effect modifier. Consequently, the shared (conditional) effect modifier assumption holds [1]}. The main treatment coefficient \(\beta _t=-2\)  is considered a strong conditional treatment effect versus the control at baseline (when the covariate values are zero).
